Short attention span theater
That $200-a-month AI plan is hiding something on us
I’ve figured out something about my $200-a-month AI subscriptions: I’m getting more out of them in tokens alone than I’m paying for.
Duh.
If I were on pay-per-token, I’d spend heaps more. It’s a simple arbitrage, right? The labs know exactly what they’re doing. They’re getting us all using. They want us all locked in, baked in, unable to imagine our days without it.
Again, duh.
Well, it’s working and it’s hiding something obvious and something not-so-obvious.
The flat rate is masking two things.
The real cost of inference
The real cost of all this starting without finishing
Unfinished business
I’ve started I don’t know how many things this year, burning who-knows-how-many tokens on projects and ideas that were dead on arrival.
I’ve spent nights still churning tokens at 9, 10, 11pm. The 1am sessions stopped recently – mostly because I looked up and realized I was sitting on a pile of half-baked ideas that hadn’t created value for anyone.
The thing nobody told me about how cheap it is to start things is that cheap starts don’t make the downstream work any cheaper. They just mean you start more things, which means more downstream work.
More than meets the eye
Think about what one feature release actually requires:
Updated documentation
Release notes
Write something into What’s New
Notify existing customers
Update the website – maybe that touches pricing, maybe it changes the support model
Train support
Brief customer success: what this is, what to look for, how to talk about it, how to help customers use it
Tell sales: what’s new, what it unlocks, the messaging
That’s one feature.
We published 31 workflows on Accoil recently. In my head, every single one already has its own page, its own content moment, probably its own LinkedIn posts. The building happened fast. The launch planning didn’t happen at all – I didn’t have parallel teams running that in the background while engineering (ahem Claude) shipped.
So now there’s a list that’s longer than the thing I built, sitting there waiting.
A growth-ops leader at one of the loudest AI-forward SaaS companies put it this way: AI didn’t make the work go away. It’s shape-shifting.
What does lean really mean?
I believe teams will be leaner, smaller with AI taking on a lot of the work. But as I reflect on my own workload — I’m well past 1.0 FTE in any given week — the question I keep coming back to is whether adding another human just means another orchestrator producing more efficient, higher-volume work that expands on itself.
See the workflows example above.
A mate in my AI mastermind is working on an interesting answer to the hours problem. He’s building the Night Shift. He wants to hand off at the end of his actual workday to a local machine that keeps running until the task is done. It’s smart.
I think he’s also more disciplined than me when it comes to boundaries, so it should work for him.
The Night Shift isn’t about starting more things. It’s about finishing more things.
Short attention span theater
Building a Night Shift doesn’t address the core issue of building indiscriminately.
Lots of AI work has become what I’d call short attention span theater. Like a dog who just can’t stop chasing a thrown ball, I ask myself over and over again:
What can I build today?
What can I build today?
The real question I should ask — the one that should be the first question I ask — is “What can I complete today?”
This is the right question because it forces me to think about how I’m going to use this thing I’m building to deliver or harvest value.
Endless tokens?
Let’s think about what happens when the flat-rate-Max-20x-Pro plan goes away.
If inference starts pricing at real cost, if more of us move to pay-per-token at API rates, usage costs escalate fast. The minute I have to watch a token counter, I’m drawing a much harder line on what we all get to build and experiment with.
What are we building? Why? Who’s it for? What does it deliver to customers and to the company? What’s the return and the timeline on that return?
That forced discipline is probably a good thing. Because right now, a lot of really sh*t ideas are getting built. I’m talking about myself. Just because a project has good potential doesn’t mean it’ll realize that potential if we don’t finish the damn thing.
PMBOK - really?
The fix isn’t pulling back on the tooling. The fix is the completion principle.
Real projects have a start date and an end date. They have a clearly defined scope and a definition of what gets delivered.
Projects have a stated objective: is this growth, is this operations, is this finance? And they have a way to measure whether they worked. This is not a new idea.
I hate to say it, but this is PMBOK. Project management fundamentals. The stuff that existed long before we could go from idea to working prototype in 17 minutes.
True story: A long time ago, I studied to become a PMP (project management professional). I was Big PMP’n.
We dropped this old school idea of finishing work because starting got so frictionless. This is vibe coding when it reaches its end — things get vibed into being and then left to ride those vibes.
It doesn’t work. Feelings/vibes fade usually well before we feel like doing the hard work that inevitably follows.
Wrapping it all up
So before I prompt Claude with another new idea, I now have to prompt myself:
What does success look like?
What am I trying to accomplish?
What’s the scope?
What does done mean beyond the build?
If the idea is a good one, it goes into a repository — not an immediate prompt-frenzied-sprint. Park it. Run a sanity check. Cull what doesn’t make sense anymore. Pick the best one. Work it to completion.
A feature that ships but nobody knows about didn’t really ship. Half-baked does nobody any good. At some point we all need to stop playing and start building things that are really, really high impact.
The $200 plan won’t be $200 forever. When the bill comes due, let’s have something to show for it.
Peter
PS: If you already don’t waste a bunch of tokens chasing a new idea every day, good for you. This was really a letter to my AI-addled goldfish brain to calm down and think about the reason of work again. Good on you and thanks for reading.